Irregular identification of structural models with nonparametric unobserved heterogeneity

Juan Carlos Escanciano

Journal of Econometrics, 2023, vol. 234, issue 1, 106-127

Abstract: One of the most important empirical findings in microeconometrics is the pervasiveness of heterogeneity in economic behavior (cf. Heckman, 2001). This paper shows that cumulative distribution functions and quantiles of the nonparametric unobserved heterogeneity have an infinite efficiency bound in many structural economic models of interest. The paper presents general and precise conditions to prove such results. The usefulness of the theory is demonstrated with several relevant examples in economics, including, among others, the proportion of individuals with severe long term unemployment duration, Average Marginal Effects (AME) in a correlated random coefficient model without monotonicity, and the distribution and quantiles of random coefficients in linear, binary and the popular semiparametric Mixed Logit model.

Keywords: Irregular identification; Semiparametric models; Nonparametric unobserved heterogeneity (search for similar items in EconPapers)
JEL-codes: C14 C31 C33 C35 (search for similar items in EconPapers)
Date: 2023
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Related works:
Working Paper: Irregular Identification of Structural Models with Nonparametric Unobserved Heterogeneity (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:234:y:2023:i:1:p:106-127

DOI: 10.1016/j.jeconom.2021.11.016

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